
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "150"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 136 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 131 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	34.110477	18.191747	70.021557	82.450668	21.830056	26.846503	40.096399	32.359824	0.0577	0.0700	0.0088	1.362062	1.334218
2459593	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	28.683512	17.194554	81.342711	88.150998	31.167331	37.415873	25.051066	12.632440	0.0554	0.0613	0.0034	1.325161	1.299173
2459592	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	2.533217	1.521941	7.031703	8.888837	2.555799	2.714615	4.090599	0.669153	0.1654	0.1701	0.0149	nan	nan
2459591	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	27.603935	19.533801	95.928715	102.271596	26.996473	32.580283	13.860335	2.595667	0.0536	0.0582	0.0024	1.333786	1.340482
2459590	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	34.626067	24.003907	88.929056	95.279404	28.931600	35.060275	20.716852	6.282665	0.0522	0.0574	0.0037	1.326802	1.281149
2459589	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	31.105284	21.269158	82.758807	88.295106	17.013509	22.445653	24.119511	17.872882	0.0527	0.0592	0.0044	1.323591	1.299301
2459588	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	35.682184	16.522450	97.341712	108.064757	22.325917	25.037444	24.728020	13.406101	0.0551	0.0634	0.0057	1.346430	1.339901
2459587	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	29.230427	21.251471	134.542707	144.156427	7.094028	8.882149	21.445597	16.611905	nan	nan	nan	1.500919	1.506805
2459586	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	27.087235	18.032960	31.509869	33.185935	10.015708	11.533471	24.263038	7.004523	0.0452	0.0485	0.0013	1.327132	1.280010
2459585	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	27.360061	25.563753	10.348531	11.738859	8.918408	9.968185	9.429660	6.502798	0.1298	0.1433	0.0152	0.000000	0.000000
2459584	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	24.552454	24.975171	112.294933	118.647864	15.609161	18.272246	30.769680	30.891580	0.0426	0.0430	0.0009	1.619101	1.604595
2459583	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459582	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	15.925234	16.392001	31.458095	33.459204	23.803989	28.486704	1.039571	1.497457	0.0506	0.0515	0.0011	1.301790	1.297714
2459581	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	22.181716	22.982563	36.426198	37.768812	18.830430	22.860363	1.400869	1.566224	0.0549	0.0572	0.0008	1.371447	1.370300
2459580	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	16.953747	17.480715	36.575223	38.677647	20.865095	24.213135	0.838753	1.314241	0.0537	0.0551	0.0009	1.333683	1.310825
2459579	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	16.704573	17.316539	41.412671	43.933967	23.313894	27.477402	2.965096	3.506121	0.0500	0.0517	0.0010	1.267070	1.263086
2459578	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	1.940753	1.581768	3.277976	3.614627	1.270118	1.542909	4.434391	5.630547	0.1476	0.1504	0.0144	nan	nan
2459577	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	21.750985	22.336021	33.810442	35.270054	20.772055	25.114516	1.198251	1.597443	0.0538	0.0562	0.0010	1.336445	1.333059
2459576	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	16.347526	16.238853	25.704263	27.072489	18.983878	22.096460	1.967669	2.107146	0.0533	0.0567	0.0008	1.262844	1.269921
2459575	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	17.059119	17.933118	26.641543	28.124913	15.710687	17.135990	7.288595	6.340239	0.0581	0.0627	0.0017	1.205362	1.204412
2459574	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	15.940248	16.439426	25.564513	26.885098	20.566626	24.343157	1.845295	1.553758	0.0506	0.0528	0.0008	1.252462	1.252662
2459573	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	16.695922	16.816212	44.023883	46.297149	24.644086	28.298147	2.257906	3.151684	0.0520	0.0533	0.0013	1.239040	1.233035
2459572	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	16.526851	16.968569	25.676414	27.043121	15.805215	18.170254	4.204592	5.253754	0.0563	0.0590	0.0008	1.364056	1.359628
2459571	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	nan	nan
2459570	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	20.870653	19.294870	27.255119	28.536748	1.277619	1.813311	4.529737	4.873687	0.0587	0.0647	0.0032	0.000000	0.000000
2459569	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	21.106228	20.211236	33.760244	35.060385	10.507116	10.872125	8.323612	9.008697	0.0680	0.0814	0.0071	1.306831	1.310535
2459566	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	16.260622	15.929681	33.569814	35.109186	18.910621	21.691670	0.378600	0.750407	0.0464	0.0473	0.0012	1.319342	1.315228
2459565	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459564	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	14.600011	14.538898	35.362225	37.091636	2.225803	2.395804	0.921288	1.281580	0.0516	0.0550	0.0016	1.323002	1.301734
2459563	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	16.675236	16.359009	67.571206	70.763615	19.584918	22.307662	1.946894	2.452923	0.0537	0.0559	0.0014	1.315398	1.322515
2459562	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	10.701470	10.451707	17.469728	18.332588	2.464612	2.715687	1.300999	1.630468	0.0524	0.0551	0.0009	1.301301	1.291749
2459561	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	11.460625	11.218671	16.660873	17.487780	2.794082	2.977638	2.072903	2.508500	0.0493	0.0517	0.0010	1.280819	1.278975
2459560	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459559	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	13.310629	13.064644	18.657896	19.442671	2.836496	3.398635	1.744163	2.110371	0.0527	0.0551	0.0009	1.284945	1.272950
2459558	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	18.084678	17.252667	35.057495	37.233166	21.523228	23.376349	2.352040	2.877068	0.0502	0.0522	0.0010	1.313089	1.293770
2459557	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.1594	0.1556	0.0185	nan	nan
2459556	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	18.700907	17.923057	37.843025	40.275682	19.438447	21.069611	5.196495	6.917840	0.0482	0.0493	0.0005	1.313086	1.304040
2459554	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0510	0.0519	0.0011	nan	nan
2459553	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0560	0.0559	0.0011	nan	nan
2459552	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	21.542997	21.465813	51.021270	53.134382	28.905775	32.135468	4.225553	4.538240	0.0508	0.0508	0.0018	1.024324	1.021553
2459551	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	10.798358	10.447911	20.653278	21.552634	3.385627	4.233398	2.039146	2.398772	0.0486	0.0517	0.0017	1.308162	1.292450
2459550	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0801	0.1183	0.0127	nan	nan
2459549	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459542	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	22.243587	23.394277	77.604307	80.775543	1.138569	1.995913	1.703595	2.050739	0.0555	0.0664	0.0070	1.380723	1.359417
2459541	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	10.269544	10.001782	36.162100	37.548538	260.589773	270.946148	21.184860	16.630872	0.0501	0.0579	0.0054	1.329253	1.326438
2459540	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	14.942948	16.714506	17.403719	18.464342	4.014278	5.159323	1.143415	1.469110	0.0546	0.0607	0.0048	1.292704	1.281068
2459536	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	27.705507	27.950414	66.330051	68.839279	29.371837	31.557489	4.588030	4.890457	0.0486	0.0491	0.0014	0.000000	0.000000
2459535	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	11.693638	13.126725	16.185956	16.962257	2.247287	5.487979	0.761909	1.211344	0.0625	0.0653	0.0054	1.078245	1.079857
2459534	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	12.276749	13.435718	15.055209	15.708450	2.267368	3.825227	0.615904	0.728334	0.0526	0.0540	0.0050	0.000000	0.000000
2459533	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	18.955358	20.097686	35.872101	37.661502	17.884346	20.702238	2.485582	3.431427	0.0467	0.0470	0.0014	0.000000	0.000000
2459532	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	22.203626	23.620320	48.276790	50.967794	22.243777	25.572922	1.762206	2.328948	0.0505	0.0507	0.0013	1.199431	1.178883
2459530	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459527	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459523	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459522	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459513	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	1.786130	1.508043	3.224918	3.826946	0.502590	4.444307	3.494567	5.513754	0.1357	0.1948	0.0160	nan	nan
2459508	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	27.754873	30.719197	50.666124	53.381565	18.079970	15.593079	12.889509	14.855935	0.0615	0.0801	0.0154	0.000000	0.000000
2459505	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	25.515591	31.886226	47.365298	51.559700	7.345721	10.408085	2.627022	3.623858	0.0505	0.0500	0.0045	1.305099	1.280784
2459503	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	28.613613	30.351180	83.574393	87.048609	33.874171	33.397844	3.722668	4.804079	0.0441	0.0401	0.0078	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 150 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 150, Node 15:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 150: 2459663

Antenna 150: 2459662

Antenna 150: 2459661

Antenna 150: 2459660

Antenna 150: 2459659

Antenna 150: 2459658

Antenna 150: 2459657

Antenna 150: 2459656

Antenna 150: 2459655

Antenna 150: 2459653

Antenna 150: 2459652

Antenna 150: 2459651

Antenna 150: 2459650

Antenna 150: 2459649

Antenna 150: 2459648

Antenna 150: 2459647

Antenna 150: 2459646

Antenna 150: 2459645

Antenna 150: 2459642

Antenna 150: 2459640

Antenna 150: 2459639

Antenna 150: 2459638

Antenna 150: 2459637

Antenna 150: 2459636

Antenna 150: 2459635

Antenna 150: 2459634

Antenna 150: 2459633

Antenna 150: 2459632

Antenna 150: 2459631

Antenna 150: 2459630

Antenna 150: 2459629

Antenna 150: 2459628

Antenna 150: 2459627

Antenna 150: 2459626

Antenna 150: 2459625

Antenna 150: 2459624

Antenna 150: 2459623

Antenna 150: 2459622

Antenna 150: 2459621

Antenna 150: 2459620

Antenna 150: 2459619

Antenna 150: 2459618

Antenna 150: 2459617

Antenna 150: 2459616

Antenna 150: 2459615

Antenna 150: 2459614

Antenna 150: 2459613

Antenna 150: 2459612

Antenna 150: 2459611

Antenna 150: 2459610

Antenna 150: 2459609

Antenna 150: 2459608

Antenna 150: 2459607

Antenna 150: 2459605

Antenna 150: 2459604

Antenna 150: 2459603

Antenna 150: 2459602

Antenna 150: 2459598

Antenna 150: 2459597

Antenna 150: 2459596

Antenna 150: 2459595

Antenna 150: 2459594

Antenna 150: 2459593

Antenna 150: 2459592

Antenna 150: 2459591

Antenna 150: 2459590

Antenna 150: 2459589

Antenna 150: 2459588

Antenna 150: 2459587

Antenna 150: 2459586

Antenna 150: 2459585

Antenna 150: 2459584

Antenna 150: 2459583

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶